ࡱ> s@ bjbjFF . ,,:,L3L3L383t3TYX5L9"n999g;; ;1Y3Y3Y3Y3Y3Y3Y$\R^WY9;E;"g;;;WY>>99Y,BBB;>899TB;1YBB5OhvqP9L5  nL3%@`OPY<YO_AL_ qP0>>_qP B;;;WYWY(h.AFh. Working paper for Public Management Conference in Texas A&M: Do managerial Factors Matter? Ratings of Texas Independent School District Bonds Zhirong (Jerry) Zhao, Ph.D. Assistant Professor Department of Political Science Eastern Michigan University  HYPERLINK "mailto:zhirong.zhao@emich.edu" zhirong.zhao@emich.edu Wenli Yan Martin School of Public Policy and Administration University of Kentucky  HYPERLINK "mailto:wyan3@uky.edu" wyan3@uky.edu ABSTRACT Since the 1990s, the increased volume of school district bonds has aroused the concerns on the credit quality of debt issuance. Credit ratings by agencies like Standard & Poors (S&P) and Moodys assess the likelihood that an obligor, or a specific issue by an obligor, will default on the interest or principal that are due. Many studies have been conducted to examine the factors that reflect ratings of municipal bonds. However, less research attention has been given to school district bonds. This paper aims to explore the possible association between managerial factors and the ratings of school district bonds. Using the data of 465 Texas independent school districts that receive Standard & Poors ratings on their GO bonds, the study examines whether and how managerial quality, personnel turnover, and education performance have been incorporated in measuring school districts credit quality. After controlling for socio-demographic, debt, and financial factors that are typically used in school district credit analysis, we find that personnel turnover and education performance have significant effects on school district bond ratings, but the effects are diagnostic rather than predictive. INTRDUCTION Since the last decade, school districts have been struggling to balance their operational requirements and capital improvement because of the increased infrastructure needs, which is due to rapid population growth in certain regions of the county, the need to comply with mandated disability and safety requirements and replacement of older infrastructures  ADDIN EN.CITE Berman19941263126313Berman, JulieGrading school credit quality.American City & County121092SCHOOL bondsSCHOOL districts -- FinanceUNITED States19941994/02//Primedia Business Magazines & Media Inc.0149337XArticlehttp://search.epnet.com/login.aspx?direct=true&db=aph&an=9409130437 file://localhost/Users/user/Documents/Jerry%20Zhao/Archive/Notes/Grading%20school%20credit%20quality.doc(Berman 1994). In addition, states that have historically assisted in funding school capital needs have reduced their grants and instead provided credit enhancing programs  ADDIN EN.CITE Harris20021264126417Harris, Mary H.Munley, Vincent G.Cabrini College; Lehigh U;The Sequence of Decisions Facing School District Officials in the Bond Issuing Process: A Multistage ModelJournal of Education Finance113-31281State and Local Budget and Expenditures (H720)Educational Finance (I220)Education: Government Policy (I280)Finance in Urban and Rural Economies (R510)20022002///Summer00989495http://www.uark.edu/misc/elfc/jef/home.htmlhttp://search.epnet.com/login.aspx?direct=true&db=ecn&an=0761809(Harris and Munley 2002). Therefore, more and more local school districts find it necessary and have the ability to raise debt to meet their capital needs, and the total amount of school-related borrowing nationwide has ballooned. As the following chart shows, the outstanding long-term debts of public elementary-secondary school systems has almost tripled in a about decade since 1992.  Figure 1 Indebtedness of Public Elementary-Secondary School Systems Data source: U.S. Census Bureau ( HYPERLINK "http://www.census.gov/govs/www/school.html" http://www.census.gov/govs/www/school.html) The increased volumes of school debt have aroused the concerns on the default risk, which is the likelihood that an obligor, or a specific issue by an obligor, will default on the interest or principal that are due. Although rare in number since 1930s, municipal bond defaults have caught significant press once happened, such as New York Citys default on general obligation notes in 1975 and Clevelands default on bond anticipation notes in 1978  ADDIN EN.CITE Ometer19921927192717Gary OmeterA short course in municipal credit analysisTrusts and EstatesTrusts and Estates45-48May1992(Ometer 1992). It is difficult, however, for individual investors to assess the default risk and hence credit worthiness of issuers or particular bond issues. Historically, bond rating agencies such as Moodys and Standard & Poors (S&P) have stand out to help provide this information to the investors  ADDIN EN.CITE Livingston1993171717176Livingston, MilesMoney and capital markets6392ndMoney market.Capital market.Financial instruments.International finance1993New YorkNew York Institute of Finance0130544051Main 5th floor HG226 .L58 1993(Livingston 1993). Many studies have been conducted on the process of bond rating, the determinants of bond rating, and the usefulness of bond ratings in predicting default risk and bond yields (interest costs). A rich literature has been accumulated on ratings of corporate bonds, and then extended to ratings of municipal bonds  ADDIN EN.CITE Brown1998192119216Patrick J. BrownBond markets: structures and yield calculations1998New YorkAMACOM(Brown 1998). Less research attention, however, has been given to independent school district bonds, which comprise an important portion of municipal bonds  ADDIN EN.CITE Harris20021311131132Harris, Mary H.School District Bond Finance: A Study on Bond Ratings and State Capital Aid ProgramsEducational Finance (I220)State and Local Borrowing (H740)20022002///http://search.epnet.com/login.aspx?direct=true&db=ecn&an=0621492(Harris 2002). This paper aims to explore whether and how indicators of school district managerial capacity have been incorporated by bond rating agencies in assessing potential default risk. We develop a research model which helps to capture the effects of managerial factors, controlling for socioeconomic, demographic, and fiscal factors that have been typically used in credit analysis. Using the data from 429 Texas independent school districts, we find that personnel (teacher) turnover and education performance have significant effects on bond ratings of school districts. In particular, these factors may serve as diagnostic (rather than predictive) indicators for bond raters as signals of poor management. These signals, especially when several of them are combined, may raise the concerns of rating agencies, which in turn leads to less satisfactory credit ratings. In the next two sections we describe the process of school district bond rating, and then provide a synthesis of extant literature on the determinants of these ratings. In Section IV we develop hypotheses of how managerial capacity may affect school district bond ratings. Section V presents a probit research model, and describes data sources and variables. Results of estimation are presented in Section VI, following by multiple ways to interpret the findings. Finally, in Section VII we discuss policy implications, limitations and the study, and future directions of further inquiry. RATINGS OF MUNICIPAL BONDS Independent school districts, like other municipal governments, can issue municipal bonds to borrow money, typically as long-term debt used for capital improvements. When school officials prepare to issue a bond, they much first decide whether or not to have it rated by an independent rating agency  ADDIN EN.CITE Harris20021264126417Harris, Mary H.Munley, Vincent G.Cabrini College; Lehigh U;The Sequence of Decisions Facing School District Officials in the Bond Issuing Process: A Multistage ModelJournal of Education Finance113-31281State and Local Budget and Expenditures (H720)Educational Finance (I220)Education: Government Policy (I280)Finance in Urban and Rural Economies (R510)20022002///Summer00989495http://www.uark.edu/misc/elfc/jef/home.htmlhttp://search.epnet.com/login.aspx?direct=true&db=ecn&an=0761809(Harris and Munley 2002). The two major rating services for municipal bond issues are Moodys Investors Services, Inc. (Moodys) and Standard & Poor Corporation (S&P). They rate municipal bonds upon request by the issuers (municipal governments) for an agreed upon fee. A published bond rating indicates school districts credit quality the ability and willingness to repay debt in full and on time. The two agencies use slightly different notions for different levels of credit quality, but in general the rating system can be divided into investment grade bonds (A or above) or speculative grade bonds (below), with AAA (or Aaa) being the prime level with maximum safety  ADDIN EN.CITE Harris20021264126417Harris, Mary H.Munley, Vincent G.Cabrini College; Lehigh U;The Sequence of Decisions Facing School District Officials in the Bond Issuing Process: A Multistage ModelJournal of Education Finance113-31281State and Local Budget and Expenditures (H720)Educational Finance (I220)Education: Government Policy (I280)Finance in Urban and Rural Economies (R510)20022002///Summer00989495http://www.uark.edu/misc/elfc/jef/home.htmlhttp://search.epnet.com/login.aspx?direct=true&db=ecn&an=0761809(Harris and Munley 2002). School districts care about these ratings, because bond ratings, as a measure of the risk, are presumably negatively related to interest costs of bond issuing  ADDIN EN.CITE Capeci19911731173117Capeci, JohnBrandeis UCredit Risk, Credit Ratings, and Municipal Bond Yields: A Panel StudyNational Tax Journal41-56444Descriptor: Asset Pricing -- G120State and Local Borrowing -- H740BondsMunicipalityCapital Markets--Empirical Studies, Including Regulation -- 3132Capital Markets: Theory, Including Portfolio Selection, and Empirical Studies Illustrating Theory -- 3131State and Local Government Borrowing -- 3243Geographic: U.S.1991Part 10264559 Provider: OCLCJohnson19991923192317Johnson, Craig L.State government credit quality: down, but not out!Public Administration Review243-2495931999Rubinfeld19731347134717Rubinfeld, DanielCredit ratings and the market for general obligation municipal bondsNational Tax Journal17261YieldMunicipal bondsModelsGeneral obligation bondsCreditBond ratingBond ratings1973MAR 7300280283(Capeci 1991; Johnson 1999; Rubinfeld 1973). The higher rating of a bond, the lower the risk, and the investors are willing to buy the bond with a lower interest return. Municipal bonds can be divided in two categories: general obligation and revenue bonds. General obligation (GO) bonds are backed by the full-faith and credit of the governmental body issuing them, while revenue bonds are backed from revenues of a specific, limited source  ADDIN EN.CITE Finkler2001108110816Finkler, Steven A.Financial management for public, health, and not-for-profit organizationsCharles T. Horngren series in accountingxxx, 576Finance, Public United States.Finance, Public United States Accounting.Health facilities United States Business management.Nonprofit organizations Finance.2001Upper Saddle River, N.J.Prentice Hall0130176141Main 5th floor HJ257.2 .F555 2001C:\Documents and Settings\Jerry\My Documents\zhao_2004\Prospect\Bibliography\Financial Management.doc(Finkler 2001). The focus of this study is on GO bonds, which are increasingly used by school district. According to Berman  ADDIN EN.CITE Berman19941263126313Berman, JulieGrading school credit quality.American City & County121092SCHOOL bondsSCHOOL districts -- FinanceUNITED States19941994/02//Primedia Business Magazines & Media Inc.0149337XArticlehttp://search.epnet.com/login.aspx?direct=true&db=aph&an=9409130437 file://localhost/Users/user/Documents/Jerry%20Zhao/Archive/Notes/Grading%20school%20credit%20quality.doc(Berman), 85% of all school district debt rated by Moodys are voter-approved, tax-supported general obligation bonds. Bond ratings can be issued by both bond issuers or particular bond issues. Because GO bonds are fully guaranteed by the government, bond rating agencies typically assign the same rating to all GO bonds by a governmental entity (at a time), because they carry the same level of risk  ADDIN EN.CITE Ingram19831740174017Ingram, Robert W.Brooks, Leroy D.Copeland, Ronald M.The Information Content of Municipal Bond Rating Changes: A NoteJournal of Finance997-1003383Descriptor: Capital Markets--Empirical Studies, Including Regulation -- 3132Geographic: U.S.1983June0149141 Provider: OCLC(Ingram, Brooks, and Copeland 1983). DETERMINANTS OF MUNICIPAL BOND RATINGS Rating municipal bonds is a complicated process. Both Moodys and S&P have published their philosophy and criteria in rating bonds. Typically, they claim that the ratings are based on information on the governments financial, debt, economic, and administrative conditions  ADDIN EN.CITE Johnson20051909190917Johnson, Craig L.Kriz, Kenneth A.In u; u neFiscal Institutions, Credit Ratings, and Borrowing CostsPublic Budgeting and Finance84-103251Descriptor: Investment BankingVenture CapitalBrokerage -- G240State and Local GovernmentIntergovernmental Relations: General -- H700State and Local Borrowing -- H740BudgetDebtGovernmentGeographic: U.S.2005Spring0774640 Provider: OCLC(Johnson and Kriz 2005). In addition, some argues that Moodys focuses more on outstanding debt and S&P focuses more on the economic base of the issuing entity  ADDIN EN.CITE Harris20021264126417Harris, Mary H.Munley, Vincent G.Cabrini College; Lehigh U;The Sequence of Decisions Facing School District Officials in the Bond Issuing Process: A Multistage ModelJournal of Education Finance113-31281State and Local Budget and Expenditures (H720)Educational Finance (I220)Education: Government Policy (I280)Finance in Urban and Rural Economies (R510)20022002///Summer00989495http://www.uark.edu/misc/elfc/jef/home.htmlhttp://search.epnet.com/login.aspx?direct=true&db=ecn&an=0761809Cluff19841341134117Cluff, George S.Farnham, Paul G.Standard & Poor's vs. Moody's: Which City Characteristics Influence Municipal Bond Ratings?The Quarterly review of economics and business.72243Statistical analysisMunicipal bondsCitiesBond ratingBond ratings1984Autumn00335797(Harris and Munley 2002; Cluff and Farnham 1984). A considerable literature has developed about the determinants of bond ratings, trying to use statistical models to duplicate bond agencies ratings  ADDIN EN.CITE Ang19751926192617James S. AngKiritkumar A. PatelBond rating methods: comparison and validationThe journal of financeThe journal of finance631-640XXX21975(Ang and Patel 1975), to compare ratings from multiple agencies  ADDIN EN.CITE Morton19751726172617Morton, T. GregoryA Comparative Analysis of Moody's and Standard and Poor's Municipal Bond RatingsReview of Business and Economic Research74-81112Descriptor: Capital Markets--Empirical Studies, Including Regulation -- 3132State and Local Government Borrowing -- 3243Geographic: U.S.19750090154 Provider: OCLCJohnson19991923192317Johnson, Craig L.State government credit quality: down, but not out!Public Administration Review243-2495931999(Morton 1975; Johnson 1999), or to general insights that may be used to assess credit quality of unrated bonds  ADDIN EN.CITE Carleton19691832183217Carleton, Willard T.Lerner, Eugene M.Statistical Credit Scoring of Municipal BondsJournal of Money, Credit and Banking750-764141969Nov.http://links.jstor.org/sici?sici=0022-2879%28196911%291%3A4%3C750%3ASCSOMB%3E2.0.CO%3B2-7 (Carleton and Lerner 1969). In this line of inquiry, there seems to be a traceable path of historic evolution. At the beginning, not long after the 1930s, when there was a long record of municipal bond defaults, the most important information for municipal bond analysis was the historical accounting record of the community in question  ADDIN EN.CITE Carleton19691832183217Carleton, Willard T.Lerner, Eugene M.Statistical Credit Scoring of Municipal BondsJournal of Money, Credit and Banking750-764141969Nov.http://links.jstor.org/sici?sici=0022-2879%28196911%291%3A4%3C750%3ASCSOMB%3E2.0.CO%3B2-7 (Carleton and Lerner 1969). In the 1970s and 1980s, defaults of municipal bond had largely become long-ago stories, and the focus of credit assessment shifted to a heavy reliance on financial accounting variables, such as revenue, per capita debt, or debt as a percentage of property tax value  ADDIN EN.CITE Loviscek19901720172017Loviscek, Anthony L.Crowley, Frederick D.Indiana U-Purdue U; Indiana U-Purdue UWhat Is in a Municipal Bond Rating?Financial Review25-53251Descriptor: Capital Markets--Empirical Studies, Including Regulation -- 3132State and Local Government Borrowing -- 3243Geographic: U.S.1990February0231046 Provider: OCLC(Loviscek and Crowley 1990). By 1990 over 70 different financial accounting variables had been specified, and many of them had been demonstrated as associated with municipal bond ratings, mostly through Discriminant analysis  ADDIN EN.CITE Wallace19811904190417Wallace, Wanda A.The Association between Municipal Market Measures and Selected Financial Reporting PracticesJournal of Accounting Research502-5201921981Autumnhttp://links.jstor.org/sici?sici=0021-8456%28198123%2919%3A2%3C502%3ATABMMM%3E2.0.CO%3B2-D Ingram19821903190317Ingram, Robert W.Copeland, Ronald M.Municipal Market Measures and Reporting Practices: An ExtensionJournal of Accounting Research766-772202, Part II1982Autumnhttp://links.jstor.org/sici?sici=0021-8456%28198223%2920%3A2%3C766%3AMMMARP%3E2.0.CO%3B2-B Wilson19841905190517Wilson, Earl R.Howard, Thomas P.The Association Between Municipal Market Measures and Selected Financial Reporting Practices: Additional EvidenceJournal of Accounting Research207-2242211984Springhttp://links.jstor.org/sici?sici=0021-8456%28198421%2922%3A1%3C207%3ATABMMM%3E2.0.CO%3B2-D (Wallace 1981; Ingram and Copeland 1982; Wilson and Howard 1984). Nevertheless, these studies in general had low success rates in predicting the actual bond ratings  ADDIN EN.CITE Michel19771724172417Michel, Allen J.Municipal Bond Ratings: A Discriminant Analysis ApproachJournal of Financial and Quantitative AnalysisJournal of financial and quantitative analysis587-98124Descriptor: Capital Markets--Empirical Studies, Including Regulation -- 3132State and Local Government Borrowing -- 3243Geographic: U.S.1977Nov.0098565 Provider: OCLC(Michel 1977). It seems that there have been a paradigm change since the early 1990s about studies on municipal bond ratings. Unlike the traditional approach of Discriminant analysis, many studies instead use regressions, in particular nonlinear categorical logit/probit regressions, to estimate causal models of municipal bond rating  ADDIN EN.CITE Loviscek19901720172017Loviscek, Anthony L.Crowley, Frederick D.Indiana U-Purdue U; Indiana U-Purdue UWhat Is in a Municipal Bond Rating?Financial Review25-53251Descriptor: Capital Markets--Empirical Studies, Including Regulation -- 3132State and Local Government Borrowing -- 3243Geographic: U.S.1990February0231046 Provider: OCLCFeroz19921746174617Feroz, Ehsan H.Wilson, Earl R.Market Segmentation and the Association between Municipal Financial Disclosure and Net Interest CostsAccounting Review480-495673Market segmentation, Marketability, Financial disclosure, Municipal bonds1992Jul.http://links.jstor.org/sici?sici=0001-4826%28199207%2967%3A3%3C480%3AMSATAB%3E2.0.CO%3B2-Z Gist19921325132517Gist, Willie E.The Market for School District Bonds: An Empirical Analysis of Texas Independent School DistrictsSouthwest Journal of Business and Economics3191TrendsStudiesSchool districtsMunicipal bondsEconomic modelsCorrelation analysisBond ratings1992Spring87504294Johnson20051909190917Johnson, Craig L.Kriz, Kenneth A.In u; u neFiscal Institutions, Credit Ratings, and Borrowing CostsPublic Budgeting and Finance84-103251Descriptor: Investment BankingVenture CapitalBrokerage -- G240State and Local GovernmentIntergovernmental Relations: General -- H700State and Local Borrowing -- H740BudgetDebtGovernmentGeographic: U.S.2005Spring0774640 Provider: OCLC(Loviscek and Crowley 1990; Feroz and Wilson 1992; Gist 1992; Johnson and Kriz 2005). Typically, these studies go beyond accounting variables, and include variables reflecting economic base and expansion  ADDIN EN.CITE Loviscek19901720172017Loviscek, Anthony L.Crowley, Frederick D.Indiana U-Purdue U; Indiana U-Purdue UWhat Is in a Municipal Bond Rating?Financial Review25-53251Descriptor: Capital Markets--Empirical Studies, Including Regulation -- 3132State and Local Government Borrowing -- 3243Geographic: U.S.1990February0231046 Provider: OCLC(Loviscek and Crowley 1990), socio-demographic factors such as population and race composition  ADDIN EN.CITE Gist19921325132517Gist, Willie E.The Market for School District Bonds: An Empirical Analysis of Texas Independent School DistrictsSouthwest Journal of Business and Economics3191TrendsStudiesSchool districtsMunicipal bondsEconomic modelsCorrelation analysisBond ratings1992Spring87504294Simonsen20011272127217Simonsen, BillRobbins, Mark D.Helgerson, LeeInstitute of Public Affairs, U CT; OR State Treasury;The Influence of Jurisdiction Size and Sale Type on Municipal Bond Interest Rates: An Empirical AnalysisPublic Administration Review709-17616State and Local Borrowing (H740)20012001/11//Nov.-Dec. 200100333352http://www.blackwellpublishing.com/journal.asp?ref=0033-3352http://search.epnet.com/login.aspx?direct=true&db=ecn&an=0601235(Gist 1992; Simonsen, Robbins, and Helgerson 2001), and institutional constrains  ADDIN EN.CITE Johnson20051909190917Johnson, Craig L.Kriz, Kenneth A.In u; u neFiscal Institutions, Credit Ratings, and Borrowing CostsPublic Budgeting and Finance84-103251Descriptor: Investment BankingVenture CapitalBrokerage -- G240State and Local GovernmentIntergovernmental Relations: General -- H700State and Local Borrowing -- H740BudgetDebtGovernmentGeographic: U.S.2005Spring0774640 Provider: OCLC(Johnson and Kriz 2005). In addition, studies that are focused on school district bond ratings also take into account some unique characteristics of school districts, including year-end fund balance  ADDIN EN.CITE Harris20021311131132Harris, Mary H.School District Bond Finance: A Study on Bond Ratings and State Capital Aid ProgramsEducational Finance (I220)State and Local Borrowing (H740)20022002///http://search.epnet.com/login.aspx?direct=true&db=ecn&an=0621492(Harris 2002), student enrollment  ADDIN EN.CITE Harris20021311131132Harris, Mary H.School District Bond Finance: A Study on Bond Ratings and State Capital Aid ProgramsEducational Finance (I220)State and Local Borrowing (H740)20022002///http://search.epnet.com/login.aspx?direct=true&db=ecn&an=0621492(Harris 2002), average daily attendance  ADDIN EN.CITE Grubb19771907190717Grubb, W. NortonOsman, Jack W.The Causes of School Finance Inequalities: Serrano and the Case of CaliforniaPublic Finance Quarterly373-9253Descriptor: Economics of Education -- 9120State and Local Government Finance--General -- 3240Geographic: U.S.1977July0100437 Provider: OCLCPopp19791906190617Popp, DeanVogt, WalterAlternative Methods of School Finance: An Empirical Analysis of Cities in San Diego CountyAmerican Journal of Economics and Sociology337-48384Descriptor: State and Local Government Finance--General -- 3240Economics of Education -- 91201979Oct.0112084 Provider: OCLCGist19921325132517Gist, Willie E.The Market for School District Bonds: An Empirical Analysis of Texas Independent School DistrictsSouthwest Journal of Business and Economics3191TrendsStudiesSchool districtsMunicipal bondsEconomic modelsCorrelation analysisBond ratings1992Spring87504294(Grubb and Osman 1977; Popp and Vogt 1979; Gist 1992), and percentage of minority students  ADDIN EN.CITE Gist19921325132517Gist, Willie E.The Market for School District Bonds: An Empirical Analysis of Texas Independent School DistrictsSouthwest Journal of Business and Economics3191TrendsStudiesSchool districtsMunicipal bondsEconomic modelsCorrelation analysisBond ratings1992Spring87504294Popp19791906190617Popp, DeanVogt, WalterAlternative Methods of School Finance: An Empirical Analysis of Cities in San Diego CountyAmerican Journal of Economics and Sociology337-48384Descriptor: State and Local Government Finance--General -- 3240Economics of Education -- 91201979Oct.0112084 Provider: OCLCHarris20021264126417Harris, Mary H.Munley, Vincent G.Cabrini College; Lehigh U;The Sequence of Decisions Facing School District Officials in the Bond Issuing Process: A Multistage ModelJournal of Education Finance113-31281State and Local Budget and Expenditures (H720)Educational Finance (I220)Education: Government Policy (I280)Finance in Urban and Rural Economies (R510)20022002///Summer00989495http://www.uark.edu/misc/elfc/jef/home.htmlhttp://search.epnet.com/login.aspx?direct=true&db=ecn&an=0761809(Gist 1992; Popp and Vogt 1979; Harris and Munley 2002), etc. The increased number of variables from multiple perspectives indicates an accumulation of knowledge about the determinants of municipal bond ratings. With such a progress, some would hope that we can predict the actual bond ratings with reasonable accuracy. However, Wilson and Howard  ADDIN EN.CITE Wilson19841905190517Wilson, Earl R.Howard, Thomas P.The Association Between Municipal Market Measures and Selected Financial Reporting Practices: Additional EvidenceJournal of Accounting Research207-2242211984Springhttp://links.jstor.org/sici?sici=0021-8456%28198421%2922%3A1%3C207%3ATABMMM%3E2.0.CO%3B2-D (1984) warms that there is no objective measure of credit ratings, because the process of assigning rating combines significant qualitative effort. This statement had been confirmed by the rating agencies which insist that they consider subjective factors that cannot be quantified, and they consider more variables than a statistical model be incorporate  ADDIN EN.CITE Ederington19851749174917Ederington, Louis H.Classification Models and Bond RatingsFinancial Review237-62204Descriptor: Capital Markets--Empirical Studies, Including Regulation -- 3132Geographic: U.S.1985November0187185 Provider: OCLC(Ederington 1985). Indeed, qualitative factors have been nearly ignored by the efforts of statistical modeling in the past literature. In this paper, however, we hold the proposition that qualitative factors such as managerial capacity are not necessarily unquantifiable, are not necessarily non-objective, and can be incorporated and examined. PUBLIC MANAGEMENT AND SCHOOL BOND RATINGS Although Moodys and S&P have independent rating philosophy and rating process, each identifies essentially four principal credit factors of municipal bond rating  ADDIN EN.CITE Gist19921325132517Gist, Willie E.The Market for School District Bonds: An Empirical Analysis of Texas Independent School DistrictsSouthwest Journal of Business and Economics3191TrendsStudiesSchool districtsMunicipal bondsEconomic modelsCorrelation analysisBond ratings1992Spring87504294(Gist 1992): economic factors, debt factors, fiscal/financial factors, and managerial(administrative) factors. Both Moodys and S&P acknowledge that management factors are the most difficult to assess because they are not easily quantifiable  ADDIN EN.CITE Grourke20041930193027Joan E. GrourkeMunicipal bond ratingsCity and Town2004Division of Local Services, Massachusetts Department of Revenue(Grourke 2004), so it depends mostly through bond raters qualitative impression about the effectiveness of the governing process to management performance and address problems  ADDIN EN.CITE Standard & Poor's2002192919296Standard & Poor's,Public Finance Criteria2002New YorkStandard & Poor's(Standard & Poor's 2002). It is for the same reason that managerial factors have been mostly neglected in the past literature while all the other factors have been extensively examined. Simonsen et al.  ADDIN EN.CITE Simonsen20011272127217Simonsen, BillRobbins, Mark D.Helgerson, LeeInstitute of Public Affairs, U CT; OR State Treasury;The Influence of Jurisdiction Size and Sale Type on Municipal Bond Interest Rates: An Empirical AnalysisPublic Administration Review709-17616State and Local Borrowing (H740)20012001/11//Nov.-Dec. 200100333352http://www.blackwellpublishing.com/journal.asp?ref=0033-3352http://search.epnet.com/login.aspx?direct=true&db=ecn&an=0601235(2001) provide one among a few exceptions. However, in this study management capacity is narrowed down to financial management, which is then measured by jurisdiction size as a proxy. Conceding the limitation of this approach, Simonsen et al. argue that a logical extension of the study would be to incorporate additional measures of management capacity into the model  ADDIN EN.CITE Simonsen20011272:715127217Simonsen, BillRobbins, Mark D.Helgerson, LeeInstitute of Public Affairs, U CT; OR State Treasury;The Influence of Jurisdiction Size and Sale Type on Municipal Bond Interest Rates: An Empirical AnalysisPublic Administration Review709-17616State and Local Borrowing (H740)20012001/11//Nov.-Dec. 200100333352http://www.blackwellpublishing.com/journal.asp?ref=0033-3352http://search.epnet.com/login.aspx?direct=true&db=ecn&an=0601235(Simonsen, Robbins, and Helgerson 2001:715). In this study, we will explore the possible association between municipal bond ratings and three managerial factors managerial quality, personnel turnover, and managerial performance. We develop the hypotheses based on a formal model on the impact of public management by OToole and Meier  ADDIN EN.CITE O'Toole19991766176617Laurence J O'TooleKenneth J MeierModeling the impact of public management: Implications of structural contextJournal of Public Administration Research and Theory5059Oct1999(1999), and test the hypotheses on a sample of Texas school districts that have obtained GO bond rating form Standard & Poor in recent years. The base model: The OToole and Meier (OM) Model is constructed from an analysis of the mass of theoretical and empirical (mostly case-study) material on public management and performance, as well as on some of the prominent notions of how management might matter in complex, or networked, institutional settings (see OToole 2000). In seeking to understand the relationship among public management, institutional arrangements, and public program performance, the basic OM model is expressed as the following: Ot = 1(S+M1)Ot-1 + 2(Xt/S)(M3/M4) + t Where O is some measure of outcome, S is a measure of stability, M (M1, M3, and M4) denotes multiple measure managerial actions; X is a vector of environmental forces,  is an error term. The other subscripts denote time periods, and 1 and 2 are estimable parameters. Managerial quality: The OM model contains several functions of management, including internal management (M1), efforts to exploit opportunities (M3), and efforts to buffer environmental shocks (M4). In addition, implicit in the model there is a factor of Managerial quality (Mq), which is a measure designed to assess how well superintendents perform their jobs. It may be a daunting obstacle to quantify managerial quality in a large-N analysis, but Meier and OToole  ADDIN EN.CITE Meier20021764literature2006.enlEndNote176417<style face="normal" font="default" size="100%">Public management and organizational performance: The effect of managerial quality</style>(Meier and O'Toole 2002) have developed a measure by collecting residual analysis of superintendents salaries, controlling for a set of common factors that are highly correlated with salary. In this study, it is hypothesize that high level of managerial quality will provide bond raters a positive impression about the effectiveness of the governing process ADDIN EN.CITE Standard & Poor's2002192919296Standard & Poor's,Public Finance Criteria2002New YorkStandard & Poor's(Standard & Poor's 2002), and have a positive effect on the bond rating. The hypothesis is: H1: Other things being equal, school districts with higher managerial quality have higher ratings on their GO bonds. Personnel turnover rate: The Stability term in the base model can include management stability (Sm) and workforce stability (Sw). These measures of stability not only reflect characteristics of an administrative system, but also have a managerial component in that they indicate managements contribution in the administrative system  ADDIN EN.CITE Meier20051694169436Kenneth J. MeierLaurence J. O'TooleModeling public management: Empirical Analysis of the Management-Performance Nexus2005(Meier and O'Toole 2005). In this study we focus on workforce stability (or instability) which measures the turnover rate of the core production personnel, the teachers. Teach turnover rate is a critical issue in educational practice and research because it has a negative impact on student achievements  ADDIN EN.CITE Hanushek20041918191817Hanushek, E.A.Kain, J.F.Rivkin, S.G.The revolving door: A path-breaking study of teachers in Texas reveals that working conditions matter more than salaryEducation next77-82Winter2004(Hanushek, Kain, and Rivkin 2004), and it incurs significant costs for the school district for their recruitment, training, mentoring, and benefit expenditures  ADDIN EN.CITE Texas Center for Educational Research20001931193127Texas Center for Educational Research,The cost of teacher turnover2000Austin, TXTCEA(Texas Center for Educational Research 2000). A high teacher turnover rate will provide bond raters a signal of poor management, because a prime function of management is to retain the human capital of the organization  ADDIN EN.CITE Barnard1938193219326Barnard, ChesterThe functions of executive1938Cambridge, MABelnap Press of HarvardO'Toole20031763176317Laurence J O'TooleKenneth J MeierPlus ca change: Public management, personnel stability, and organizational performanceJournal of Public Administration Research and Theory4313Jan2003(Barnard 1938; O'Toole and Meier 2003). The hypothesis is: H2: Other things being equal, school districts with higher teacher turnover rate have lower ratings on their GO bonds. Managerial performance: The OM model focuses on performance conceptualized as outputs and outcomes of public programs. Typically public programs and institutions have multiple goals, so there will be multiple measures of performance  ADDIN EN.CITE Rainey2003193819386Rainey, Hal G.Understanding and managing public organizationsThe Jossey-Bass nonprofit and public management seriesxx, 4843rdPublic administration.2003San FranciscoJossey-Bass0787965618 (alk. paper)Main 6th floor JF1351 .R27 2003http://www.loc.gov/catdir/toc/wiley032/2003006234.html (Rainey 2003). Comparing with many other public organizations, school districts performance is less complicated and relatively easier to quantify. This makes the context of school districts especially suitable for testing the association between public performance and municipal bond rating. The major performance indicators used in this study is the Accountability rating of the school districts, which was created in Texas in 1993 to accredit school districts and rate schools. The rating is developed by the Texas Education Agency (TEA), which use Texas Assessment of Academic Skills (TAAS) performance, dropout rates, and attendance level as basic indicators to rate school districts performance, and classified their performance as Exemplary (EX), Recognized (RE), Academically Acceptable (AA), or Academically Unacceptable (AU).  Statute provides monetary rewards for high performance or improvement, and also provides sanctions and remedies for poor performance. Consequently, the Accountability rating as a performance measure has a high profile and is taking serious by school districts statewide. In this study, we hypothesize that: H3: Other things being equal, school districts with higher Accountability ratings have high school district bond ratings. RESESARCH METHODS Data Sources The sample in our analysis includes 465 Texas independent school districts that have obtained General-obligation bond ratings from S&P from April 4, 2002 through April 28, 2005. Originally there are 554 Texas school bond issues in the dataset provided by S&P. We deleted the issues of short-term debts and non-GO bonds, duplicated GO bonds for a same school district,  and a couple of ambiguous cases. This leaves 465 observations as our sample for analysis. Other variables of the analysis are collected from National Center for Education Statistics (NCES) and a multi-year survey conducted by Meier and OToole  ADDIN EN.CITE Meier20021475147517Meier, Kenneth J.O'Toole, Laurence J., Jr.TX A&M U; U GA;Public Management and Organizational Performance: The Effect of Managerial QualityJournal of Policy Analysis and Management629-43214BureaucracyAdministrative Processes in Public OrganizationsCorruption (D730)Structure, Scope, and Performance of Government (H110)20022002///Fall02768739http://www3.interscience.wiley.com/cgi-bin/jhome/34787http://search.epnet.com/login.aspx?direct=true&db=ecn&an=0642913(Meier and O'Toole 2002). Model Specification The purpose of our study is to find a statistical model which will reproduce Moodys or S&Ps ratings with some accuracy, but rather to detect whether and how certain managerial factors may also play a role in the determining school districts bond ratings. We use a simple probit model to test the association between the managerial factors and the probability that a school district will have an AAA bond rating. All other controlling variables are selected according to previous literature on municipal bond ratings. As follows is the equation to be estimated: PAAA = f (M, E, D, F, S) Where M includes managerial factors; E includes economic factors; D includes demographic factors; F includes financial factors; and S is a dummy variable of state permanent fund guarantee program. Dependent Variable: The unit of analysis in our study is the individual bond ratings of Texas school districts. Since roughly 95% of all the issues in our sample are AAA ratings, we dichotomize all the ratings into two categories as the dependent variable: AAA ratings are scored as 1, otherwise 0. We want to know what contributes to the probability that a particular school bond issue will achieve a AAA rating. Because the observed dependent variable is dichotomous in nature, ordinary least squares (OLS) method is inappropriate because several conventional regression assumptions are violated. Therefore, we use a probit model to estimate the parameters. Managerial factors: We use Accountability ratings (ACCOUNT) as the major indicator of education performance. In addition, In addition, we incorporate some supplemental indicators of education performance in this study. These indicators include bottom-level output indicators (attendance and dropouts), middle-bound performance indicators (overall TAAS exam pass rate), and an elite performance indicator (percentage of college admission)  ADDIN EN.CITE Meier20051694169436Kenneth J. MeierLaurence J. O'TooleModeling public management: Empirical Analysis of the Management-Performance Nexus2005Meier20021764literature2006.enlEndNote176417<style face='normal' font='default' size='100%'>Public management and organizational performance: The effect of managerial quality</style>(Meier and O'Toole 2005; Meier and O'Toole 2002). Although some of these factors have been used in the Accountability rating, empirical tests show that there is no high level of bivariate correlation between them. Therefore, controlling for these supplemental indicators may provide additional insights without running the risk of serious methodological problems. Economic and demographic factors: The economic and demographic factors we look at are total enrollment (ENROLL), the percent of nonwhite students (NONWHITE), and the percent of low income students (LOWINC). Financial factors: Financial measures include the percent of revenue from local sources (PCTLOC), the percent of the surplus funds balance (PFUNDBAL), and the ratio of net debt to taxable property value (DEBT_TAX), total revenue per pupil (REVPUPIL), and total taxable property value per pupil (TAXPUPIL). State permanent fund guarantee program We add a dummy variable, GARANTEED, to indicate whether a particular bond issue is backed by the Texas Permanent School Fund (PSF). The PSF works as a credit enhancement program as it guarantees to use a set-aside state fund to back school district debt. Therefore, PSF-backed issues will generally receive the credit rating of Texas state government, which is AAA by S&P. RESEARCH FINDINGS Table 1 and 2 provide definitions of the variables and a summary of descriptive statistics. Note that the dependent variable is very skewed toward the right side, with about 95 percent of school districts receiving an AAA bond rating. Moreover, we notice the same pattern with GARANTEED. As the two variables are highly corrected, it is clear that the high overall bond rating is mostly attributed to the state permanent fund guarantee program. Although probit model can still be applicable in dealing with a data set like this  ADDIN EN.CITE Long2001103410346Long, J. ScottFreese, JeremyRegression models for categorical dependent variables using Stataxvi, 341Regression analysis.Social sciences Statistical methods Data processing.2001College Station, Tex.Stata Press1881228622 (pap.)Science 3rd floor QA278.2 .L66 2001C:\Documents and Settings\Jerry\My Documents\zhao_2004\Prospect\Bibliography\regression models for categorical dependent variables using stata.doc(Long and Freese 2001), because of the lack of variation in the dependent variable, it is normally harder to discover associations that are significant. So the data structure suggests the chance is higher for Type II error (false negative, in that an actual association is not discovered) than Type I error (false positive, in that a nonsexist association is show mistakenly significant). Table 1: Descriptive Statistics of Variables VariableDefinitionAAAAAA rating, dummy variableMQ MQ as defined in Meier and OToole (2006)TURNOVERTeacher turnover percentageACCOUNTTexas school district Accountability ratingAPASSTAAS Exam pass rateATTENDAttendance rateDROPOUTFour-year dropout rateCOLPCTCollege admission percentageENROLLTotal enrollment of school district (thousand)NONWHITEPercentage of nonwhite studentsLOWINCPercentage of low income studentsPCTLOCPercentage of revenue from local sourcesPFUNDBALPercentage of surplus funds balanceDEDT_BASERatio of net debt to taxable property valueGARANTEEDState Permanent School Fund Guaranteed, dummy variableREVPUPILTotal revenue per pupilTAXPUPILTaxable property per pupil Table 2: Descriptive Statistics of Variables*  *: Summary statistics are presented based on 465 observations that are used in estimation. Table 3 presents the results of maximum likelihood estimation. The overall model fit is significant as identified by the Chi -squared test. Several observations stand out about the effects of managerial factors on school bond rating. First, as predicted, higher teacher turnover rate (TURNOVER) leads to lower probability of AAA rating, and the effect is significant at the 0.1 level. This finding supports the notion that credit raters may take into consideration the teacher turnover rate, either because of its associated financial costs or as a signal of poor management. Second, higher Accountability rating (ACCOUNT), as predicted, is associated with higher probability of AAA rating (at the 0.1 level). It shows that credit raters indeed take into account the effectiveness of the school district in managing education performance. With respect to the supplemental performance indicators, the coefficient of overall TAAS pass rate (APASS) is negative while that of college admission percentage (COLPCT) is positive both at the 0.1 level. These results seem confusing, but a little further reasoning provides some plausible explanation. When the ACCOUNT level is controlled, coefficients of these supplemental performance indicators actually reflect the relative priorities of different dimensions of performance a possible interpretation is that, given a level of overall education performance, school districts with better college-bound performance is perceived to be better managed than those overwhelmingly focus on TAAS pass rates. Finally, to our surprise, managerial quality (MQ) does not achieve a significant coefficient in the estimation. There may be several reasons to explain this result. For one, distinction can be made between individual-level and organization-level performance, and this may be especially the case for public agencies of which the performance is influenced by many other factors that are beyond managers control. For another, it is likely that managerial quality, being less visible than the Accountability rating or teacher turnover rate, is not easily perceived by bond raters. For instance, municipal credit analysis typically looks at the static picture of consistent performance throughout recent years, while high-quality managers impact is dynamic that shows only in incremental changes every year so a mismatch of information can easily occur. Some other findings regarding the control variables may be worth noting. First, the total enrollment (ENROLL) is negatively associated with the likelihood of an AAA rating. This may be explained by that fact that school districts undergoing rapid growth are more financially strained  ADDIN EN.CITE Rubinfeld19731347134717Rubinfeld, DanielCredit ratings and the market for general obligation municipal bondsNational Tax Journal17261YieldMunicipal bondsModelsGeneral obligation bondsCreditBond ratingBond ratings1973MAR 7300280283(Rubinfeld 1973). Second, the coefficient for the percentage of revenues coming from local sources (PCTLOC) is positive and significant at the 0.1 level, indicating that school districts that are less relying on state aid are associated with better financial outlooks, because they have high capacity to raise own-source revenues. Third, total revenue per pupil (REVPUPIL) has a significantly (0.1 level) effect on the propensity of an AAA rating. This suggest that school districts with ampler financial resources are considered to be safer targets for investment. Finally, it is not surprising to see that state permanent fund guarantee program (GARANTEED) has a very significant influence on the bond rating, as almost all school districts that are guaranteed by the state fund receive AAA ratings. Table 3: Probit Maximum Likelihood Estimations  One drawback of the probit model is the difficulty in interpreting statistical results. Unlike the case in linear regression models, the magnitude of effects in a probit model cannot be viewed directly from the coefficients. In this study, the effects of the independent variables on the likelihood of getting AAA rating are interpreted in three ways: the overall ranges of probabilities, the partial ranges of probabilities, and a graphical display of some interaction effects. The overall ranges of probabilities, given in Table 4, show the biggest impacts the independent variables can have on the possibility of receiving an AAA rating. Distinctions should be made between the estimated range and the hypothetical range. The estimated range is calculated based on the predicted probabilities of actual observations, while the hypothetical range is calculated with the assumption that the observations can have any combination of independent variables within their ranges in the sample (Long 1997). In this case, both estimated range and hypothetical range are almost 100 percent. To some extent, this result shows the models overall explanatory power. Table 4. Ranges of Probabilities for AAA RatingMaxMinRange of Pr. Estimated probabilitiesa1. 0000. 0001. 000Hypothetical probabilitiesb1. 0000. 0001. 000a. These are the maximum and minimum predicted probabilities of the observations. b. Hypothetical extremes are estimated based on the range of each individual independent variable that are significant in the estimation. The partial ranges of probabilities show the effect of each individual variable on the predicted probability, that is, the extent to which a change in a variable affects the prospect of being rated as AAA. The way to do this is to allow one variable to vary from its minimum to its maximum, with all other variables fixed at their means. The results are given in Table 5, with REVPUPIL, TURNOVER, and GARANTEED as the three most influential factors of achieving an AAA rating. For instance, other things being equal (and fixed on their mean value), school districts with the highest level of revenue per pupil has almost three times higher probability to get AAA ratings than those with the lowest level of revenue per pupil. On the other hand, the Accountability rating, although with a significant coefficient in the estimation, shows only marginal effects on the probability of AAA rating. Table 5. Partial Ranges of Probabilities for AAA Rating MaxMinRange of Pr. TURNOVER0. 500. 980. 48ACCOUNT0. 970. 980. 01APASS0. 810. 970. 16COLPCT0. 970. 980. 01ENROLL0. 880. 980. 10PCTLOC0. 950. 980. 03GARANTEED0. 980. 720. 26REVPUPIL0. 940. 340. 60 Finally, a graph is created to depict how the probability of AAA rating is affected by the two significant managerial factors: teacher turnover rate and the Accountability rating. Holding all other independent variables in their means, TURNOVER and ACCOUNT were each taken its value at the minimum, 25th percentile, mean, 75th percentile, and the maximum, and then the probabilities of AAA rating are calculated based on these schemes. In Figure 1, there are five curves, each representing a level of ACCOUNT. For each curve, data points from left to right show the probability of AAA rating when the TURNOVER take its value from its maximum to its minimum. The visualization of the results is striking. First, TURNOVER seems to matter only when it is the highest. Clearly, there is a threshold for teacher turnover rate: in most school districts, the turnover rates are normal and barely affect the bond rating; when the teacher turnover rate became extremely high, however, it catches bond raters attention and leads to low bond ratings. Moreover, ACCOUNT shows its effect only when the TURNOVER is the highest. It seems that, in most cases Accountability ratings do not matter for school district bonds. When teacher turnover rates are extremely high, however, Accountability ratings are put under close scrutiny by bond raters, and it is in this situation that it starts to affect school bond ratings. The theoretical implications of this result are threefold. First, it is clear that the effects of these managerial factors on bond ratings are nonlinear. Second, these effects are interactive rather than simply additive, as the effect of each is contingent on the other. Finally, these factors may serve as diagnostic rather than predictive indicators: when an extremely high turnover rate is combined with a very lower Accountability level, the probability of AAA rating suddenly drops -- possibly, bond raters catch the WARNING signal that something must be wrong about the school districts management.  EMBED Excel.Sheet.8  Figure 1 Effects of TURNOVER and ACCOUNT on AAA ratings. CONCLUSION In this study we try to examine the possible association between three managerial factors and the ratings of school district bonds, based on a formal model developed by OToole and Meier  ADDIN EN.CITE O'Toole19991766176617Laurence J O'TooleKenneth J MeierModeling the impact of public management: Implications of structural contextJournal of Public Administration Research and Theory5059Oct1999(1999). Using the data of 465 Texas independent school districts that receive Standard & Poors ratings on their GO bonds, we test our hypotheses on the effects of managerial factors in a probit model, holding control for other factors that have been typically used in school district credit analysis. The estimation shows that managerial quality (MQ), as measured in Meier and OToole  ADDIN EN.CITE Meier20021475147517Meier, Kenneth J.O'Toole, Laurence J., Jr.TX A&M U; U GA;Public Management and Organizational Performance: The Effect of Managerial QualityJournal of Policy Analysis and Management629-43214BureaucracyAdministrative Processes in Public OrganizationsCorruption (D730)Structure, Scope, and Performance of Government (H110)20022002///Fall02768739http://www3.interscience.wiley.com/cgi-bin/jhome/34787http://search.epnet.com/login.aspx?direct=true&db=ecn&an=0642913(2002), does not have a significant effect on the probability of AAA ratings. However, the other two hypotheses both receive support: teacher turnover rates (TURNOVER) are positively related to lower bond ratings while the Accountability ratings (ACCOUNT) show significant effects on the other direction. In addition, close examination of estimation results suggest that the effects of TURNOVER and ACCOUNT are contingent upon each other, and their implications are diagnostic rather than predictive, as these factors matter mostly at their extreme values which may be taken by bond raters as a warning signal of poor management. The study has multiple applications. First, it adds to the literature about municipal bond rating. Ratings of municipal bonds involve qualitative factors about how bond raters impression on the managerial capacity and performance of the governing body, but these claims have almost never been systematically tested in past literature. By quantifying certain managerial factors and testing them in a large-N analysis, we demonstrate some preliminary efforts to bridge that gap. Second, this study enhances our understanding of the management-performance nexus. To the extent that teacher turnover rate and education performance affect municipal bond rating, these factors indirectly affects the financial cost for school district to fund their capital improvements. So in this case there are reciprocal relationships between managerial structure, performance, and resources procurement. Moreover, the study provides hints for other subtle relations among the managerial factors, such as the distinction of individual-level management and organizational-level management, the possible crash between different dimension of performance measurements, and the nonlinear, contingent, and interactive features of managerial effects on municipal bond rating. Finally, this study has practical meanings for school districts. Knowing more about the underlying mechanism of bond rating can help school districts make a series of critical decisions  ADDIN EN.CITE Harris20021264126417Harris, Mary H.Munley, Vincent G.Cabrini College; Lehigh U;The Sequence of Decisions Facing School District Officials in the Bond Issuing Process: A Multistage ModelJournal of Education Finance113-31281State and Local Budget and Expenditures (H720)Educational Finance (I220)Education: Government Policy (I280)Finance in Urban and Rural Economies (R510)20022002///Summer00989495http://www.uark.edu/misc/elfc/jef/home.htmlhttp://search.epnet.com/login.aspx?direct=true&db=ecn&an=0761809(Harris and Munley 2002), for instance, whether to issue municipal bonds or to rely on alternative ways of financing, whether or when to obtain a municipal bond rating, whether and how to improve their municipal bond ratings. In particular, if school districts realize that high teacher turnover rate may lead to lower municipal bond rating, some of them may be more willing to spend resources to retain teachers, which in turn lead to cost savings when they issue municipal bonds. One major caveat of the study is the lack of variation in the dependent variable. We should note that the estimation results are somewhat sensitive to different model specifications. For instance, when different controlling variables are incorporated, sometimes the coefficient of ACCOUNT drops out of significance although it still maintains the expected sign. Similar situation occurs for some other controlling variables. Still, we are happy to have these findings, which we believe are not random statistical artifacts, given the high possibility of Type II error associated with this kind of data. A logical extension of this study would be to further explore the nonlinear effect of these managerial factors, the contingency between these factors, and the interaction among these factors. Furthermore, we will examine the effects of these managerial factors on the actual interest rates of municipal bonds. Then we will know whether bond rating agencies have sufficiently incorporate these factors in their ratings. REFERENCES  ADDIN EN.REFLIST Ang, James S., and Kiritkumar A. Patel. 1975. Bond rating methods: comparison and validation. The journal of finance XXX (2):631-640. Barnard, Chester. 1938. The functions of executive. Cambridge, MA: Belnap Press of Harvard. Berman, Julie. 1994. Grading school credit quality. In American City & County: Primedia Business Magazines & Media Inc. Brown, Patrick J. 1998. Bond markets: structures and yield calculations. New York: AMACOM. Capeci, John. 1991. Credit Risk, Credit Ratings, and Municipal Bond Yields: A Panel Study. National Tax Journal 44 (4):41-56. Carleton, Willard T., and Eugene M. Lerner. 1969. Statistical Credit Scoring of Municipal Bonds. Journal of Money, Credit and Banking 1 (4):750-764. Cluff, George S., and Paul G. Farnham. 1984. Standard & Poor's vs. Moody's: Which City Characteristics Influence Municipal Bond Ratings? The Quarterly review of economics and business. 24 (3):72. Ederington, Louis H. 1985. Classification Models and Bond Ratings. Financial Review 20 (4):237-62. Feroz, Ehsan H., and Earl R. Wilson. 1992. Market Segmentation and the Association between Municipal Financial Disclosure and Net Interest Costs. Accounting Review 67 (3):480-495. Finkler, Steven A. 2001. Financial management for public, health, and not-for-profit organizations, Charles T. Horngren series in accounting. Upper Saddle River, N.J.: Prentice Hall. Gist, Willie E. 1992. The Market for School District Bonds: An Empirical Analysis of Texas Independent School Districts. Southwest Journal of Business and Economics 9 (1):31. Grourke, Joan E. 2004. Municipal bond ratings. In City and Town: Division of Local Services, Massachusetts Department of Revenue. Grubb, W. Norton, and Jack W. Osman. 1977. The Causes of School Finance Inequalities: Serrano and the Case of California. Public Finance Quarterly 5 (3):373-92. Hanushek, E.A., J.F. Kain, and S.G. Rivkin. 2004. The revolving door: A path-breaking study of teachers in Texas reveals that working conditions matter more than salary. Education next (Winter):77-82. Harris, Mary H. 2002. School District Bond Finance: A Study on Bond Ratings and State Capital Aid Programs. Harris, Mary H., and Vincent G. Munley. 2002. The Sequence of Decisions Facing School District Officials in the Bond Issuing Process: A Multistage Model. Journal of Education Finance 28 (1):113-31. Ingram, Robert W., Leroy D. Brooks, and Ronald M. Copeland. 1983. The Information Content of Municipal Bond Rating Changes: A Note. Journal of Finance 38 (3):997-1003. Ingram, Robert W., and Ronald M. Copeland. 1982. Municipal Market Measures and Reporting Practices: An Extension. Journal of Accounting Research 20 (2, Part II):766-772. Johnson, Craig L. 1999. State government credit quality: down, but not out! Public Administration Review 59 (3):243-249. Johnson, Craig L., and Kenneth A. Kriz. 2005. Fiscal Institutions, Credit Ratings, and Borrowing Costs. Public Budgeting and Finance 25 (1):84-103. King, Gary, Michael Tomz, and Jason Wittenberg. 2000. Making the Most of Statistical Analyses: Improving Interpretation and Presentation. American Journal of Political Science 44 (2):346-61. Livingston, Miles. 1993. Money and capital markets. 2nd ed. New York: New York Institute of Finance. Long, J. Scott, and Jeremy Freese. 2001. Regression models for categorical dependent variables using Stata. College Station, Tex.: Stata Press. Loviscek, Anthony L., and Frederick D. Crowley. 1990. What Is in a Municipal Bond Rating? Financial Review 25 (1):25-53. Meier, Kenneth J, and Laurence J O'Toole. 2002. Public management and organizational performance: The effect of managerial quality. Journal of Policy Analysis and Management 21 (Fall):629. Meier, Kenneth J., and Laurence J. O'Toole. 2005. Modeling public management: Empirical Analysis of the Management-Performance Nexus. Meier, Kenneth J., and Laurence J. O'Toole, Jr. 2002. Public Management and Organizational Performance: The Effect of Managerial Quality. Journal of Policy Analysis and Management 21 (4):629-43. Michel, Allen J. 1977. Municipal Bond Ratings: A Discriminant Analysis Approach. Journal of Financial and Quantitative Analysis 12 (4):587-98. Morton, T. Gregory. 1975. A Comparative Analysis of Moody's and Standard and Poor's Municipal Bond Ratings. Review of Business and Economic Research 11 (2):74-81. O'Toole, Laurence J, and Kenneth J Meier. 1999. Modeling the impact of public management: Implications of structural context. Journal of Public Administration Research and Theory 9 (Oct):505. . 2003. Plus ca change: Public management, personnel stability, and organizational performance. Journal of Public Administration Research and Theory 13 (Jan):43. Ometer, Gary. 1992. A short course in municipal credit analysis. Trusts and Estates (May):45-48. Popp, Dean, and Walter Vogt. 1979. Alternative Methods of School Finance: An Empirical Analysis of Cities in San Diego County. American Journal of Economics and Sociology 38 (4):337-48. Rainey, Hal G. 2003. Understanding and managing public organizations. 3rd ed, The Jossey-Bass nonprofit and public management series. San Francisco: Jossey-Bass. Rubinfeld, Daniel. 1973. Credit ratings and the market for general obligation municipal bonds. National Tax Journal 26 (1):17. Simonsen, Bill, Mark D. Robbins, and Lee Helgerson. 2001. The Influence of Jurisdiction Size and Sale Type on Municipal Bond Interest Rates: An Empirical Analysis. Public Administration Review 61 (6):709-17. Standard & Poor's. 2002. Public Finance Criteria. New York: Standard & Poor's. Texas Center for Educational Research. 2000. The cost of teacher turnover. Austin, TX: TCEA. Wallace, Wanda A. 1981. The Association between Municipal Market Measures and Selected Financial Reporting Practices. Journal of Accounting Research 19 (2):502-520. Wilson, Earl R., and Thomas P. Howard. 1984. The Association Between Municipal Market Measures and Selected Financial Reporting Practices: Additional Evidence. Journal of Accounting Research 22 (1):207-224.   This is a preliminary draft. Please do not cite without authors consent.  The calculation and expression are based on inflation-adjusted 1990 dollars.  TEA may use slightly different base indicators or different criteria each year to assign the Accountability ratings. For details, see http://www.tea.state.tx.us/perfreport/account/  There are cases that a school district has more than one issue during the period of our study. We leave out the issues in the same school district with the same type of pledge and rating.  Net debt= long term debt (year end) + short term debt (year end)  In order to be eligible for the bond guarantee program, school districts must be accredited by the state, have bond ratings below Aaa, and have their applications approved by the Commissioner of Education. (http://www.tea.state.tx.us/psf/AR04.pdf)  In all these approaches, the probability of AAA rating based on different schemes are predicted by Clarify according to probit estimation in Table 3. The Clarify software program is created by Gary et al.  ADDIN EN.CITE King20001057105717Gary KingMichael TomzJason WittenbergMaking the Most of Statistical Analyses: Improving Interpretation and PresentationAmerican Journal of Political Science346-614422000(2000)  Note that observations with this combination of independent variables do not necessarily approximate any member of the sample (Long 1997).  Note A  2 3 4 J K   ! " ? F N Q a r % ( ) ? 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